将乐谱转为动态指板动画，帮初学者看懂小提琴按弦位置。
MusicSynth: An Automated Pipeline for Generating Violin Fingerboard Animations from Sheet Music Using Optical Music Recognition
- 用OCR识别乐谱图，自动提取音符与时间信息
- 91.2%准确率识别印刷乐谱音符，数字文件中指法正确率达99.1%
- 浏览器一键生成动画，无需安装软件
学习小提琴难在指板无标记，初学者无法直观判断按弦位置。MusicSynth 是一个开源网页工具，用户上传乐谱图片或数字文件后，自动生成逐帧显示的指板动画：每个音符在正确时刻被高亮显示。系统整合三个开源工具：光学乐谱识别（OMR）读取图像中的音符，MusicXML 解析器提取数字乐谱的时间信息，视频渲染器逐帧绘制指板画面。唯一自研部分是将音符映射到小提琴弦和指位的查找表。在 110 份公开小提琴乐谱上测试，对清晰印刷乐谱的音符识别准确率达 91.2%，在数字文件输入下指法分配正确率达 99.1%。据作者所知，目前尚无免费工具能单步完成从乐谱图像到动画教程的全自动转换。
原文摘要 · Abstract (English)
Learning the violin is harder than it looks. Unlike piano keys or guitar frets, the violin neck has no markings at all, so a beginner cannot tell by looking where to place each finger. MusicSynth is an open-source web tool that tries to fix that: user uploads a photo of any violin sheet music (or a digital score file), and the system automatically produces a video showing a violin fingerboard with each note highlighted at the right moment -- no software to install, no manual note entry required. The system connects three existing open-source tools into one pipeline: an optical music recognition (OMR) library reads the notes from the uploaded image, a MusicXML parser extracts timing information from digital scores, and a video renderer draws the fingerboard frame by frame. The only part built from scratch is the lookup table that maps each musical note to a string and finger position on the violin. Tested across 110 public-domain violin scores, MusicSynth correctly identified 91.2\,\% of notes in clean printed music and assigned the right finger position 99.1\,\% of the time when given a digital score file. To the author's knowledge, no freely available tool currently turns a sheet music image into an animated violin fingerboard tutorial automatically and in a single browser-based step.
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